PRECONDITIONED GL-CGLS METHOD USING REGULARIZATION PARAMETERS CHOSEN FROM THE GLOBAL GENERALIZED CROSS VALIDATION

In this paper, we present an e±cient way to deter- mine a suitable value of the regularization parameter using the global generalized cross validation and analyze the experimental results from preconditioned global conjugate gradient linear least squares(Gl-CGLS) method in solving image deblurring problems. Preconditioned Gl-CGLS solves general linear systems with multi-ple right-hand sides. It has been shown in [10] that this method can be e？？ectively applied to image deblurring problems. The regulariza- tion parameter, chosen from the global generalized cross validation, with preconditioned Gl-CGLS method can give better reconstruc-tions of the true image than other parameters considered in this study.